Enhanced Representative Time Periods for Transmission Expansion Planning Problems

García-Cerezo, Álvaro; García-Bertrand, Raquel; Baringo, Luis

doi:10.1109/tpwrs.2021.3067148

Cited by 16 publications

(9 citation statements)

References 13 publications

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“…Transmission capacity limits are stated by constraint (17). The spinning reserve constraint, served by thermal generators, is defined in constraint (18). Constraints (19) and (20) specify the voltage angle bounds of the slack bus and the rest buses, respectively.…”

Section: Scenario-based Tep Modelmentioning

confidence: 99%

“…Among these, scenario‐based SO is preferred due to its ability to characterize the time‐series correlation of uncertainties [20]. However, scenario reduction methods used to ease the computational burden often exclude low‐probability extreme scenarios, leading to insufficient robustness of the optimal solution [18]. To improve the robustness of the optimal solution, reference [21] introduced conditional value at risk (CVaR) in the objective function.…”

Section: Introductionmentioning

confidence: 99%

“…SO assumes that the probability distribution is known completely and uses discrete scenarios to handle the uncertainties [15], including chance-constrained [16,17] and scenario-based [18,19] methods. Among these, scenario-based SO is preferred due to its ability to characterize the time-series correlation of uncertainties [20].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An adaptive decision‐making approach for transmission expansion planning considering risk assessment of renewable energy extreme scenarios

Zhao,

Xu,

Dong

et al. 2023

IET Generation Trans & Dist

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The extreme power output scenarios of renewable energy sources (RES) proposed new challenges to the safe and stable operation of the power system. Transmission expansion planning (TEP) with large‐scale RES grid integration needs considering the risk of extreme scenarios. In this paper, an adaptive decision‐making approach for the TEP problem based on planning‐risk assessment‐replanning iterative process is proposed. The method obtains massive temporal and spatial correlated wind‐photovoltaic (PV) power output scenarios by generalizing the historical data to describe the uncertainties. A data‐driven load loss risk assessment model (RAM) based on the power system's actual operating state is built, referring to the degree of extreme scenario risks on the balance of supply and demand, and the probability of extreme scenario occurrence. The planning decision is progressively revised according to the risk assessment result. The Garver's 6‐bus system and the IEEE RTS 24‐bus system are adopted as simulation cases. The results show that the optimal expansion plans achieve a balance between the economy and robustness, which verifies the effectiveness of the proposed method.

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Section: Scenario-based Tep Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An adaptive decision‐making approach for transmission expansion planning considering risk assessment of renewable energy extreme scenarios

Zhao,

Xu,

Dong

et al. 2023

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…Authors in study [11] installed and sized the solar panels and storage systems in the transmission lines with consideration of the power loss reduction reported. The operation of the generation units in the power plants by using the unit commitment approach is proposed in [12]. In (Moreira et al, 2017), the economic dispatch approach for energy scheduling in the power plants is used.…”

Section: A Aims and Related Researchmentioning

confidence: 99%

Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants

Sun

2023

IJACSA

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The proliferation of renewable energy sources, particularly wind farms, is rapidly gaining momentum owing to their numerous benefits. Consequently, it is imperative to account for the impact of wind farms on transmission expansion planning (TEP), which is a crucial aspect of power system planning. This article presents a multi-objective optimization model that utilizes DC load flow to address the TEP challenge while also incorporating wind farm uncertainties into the model. The present study aims to optimize the expansion and planning of the TEP in the power system by considering investment and maintenance costs as objective functions. To achieve this, a multiobjective approach utilizing the shuffled frog leaping algorithm (SFLA) is proposed and implemented. The proposed objectives are simulated on the RTS-IEEE 24-bus test network. The results obtained from the proposed algorithm are compared with those of the Genetic Algorithm (GA) to assess and validate the proposed approach.

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“…SO assumes that the probability distribution is known completely and uses discrete scenarios to handle the uncertainties [15], including chance-constrained [16][17] and scenario-based [18][19] methods. Among these, scenariobased SO is preferred due to its ability to characterize the time-series correlation of uncertainties [20].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Decision-making Approach for Transmission Expansion Planning Considering Risk Assessment of Renewable Energy Extreme Scenarios

Zhao

Dong

et al. 2023

Preprint

View full text Add to dashboard Cite

The extreme power output scenarios of renewable energy sources (RES) proposed new challenges to the safe and stable operation of the power system. Transmission expansion planning (TEP) with large-scale RES grid integration needs considering the risk of extreme scenarios. In this paper, an adaptive decision-making approach for the TEP problem based on planning-risk assessment-replanning iterative process is proposed. The method obtains massive temporal and spatial correlated wind-photovoltaic (PV) power output scenarios by generalizing the historical data to describe the uncertainties. A data-driven load loss risk assessment model (RAM) based on the power system’s actual operating state is built, referring to the degree of extreme scenario risks on the balance of supply and demand, and the probability of extreme scenario occurrence. The planning decision is progressively revised according to the risk assessment result. The Garver’s 6-bus system and the IEEE RTS 24-bus system are adopted as simulation cases. The results show that the optimal expansion plans achieve a balance between the economy and robustness, which verifies the effectiveness of the proposed method.

show abstract

Enhanced Representative Time Periods for Transmission Expansion Planning Problems

Cited by 16 publications

References 13 publications

An adaptive decision‐making approach for transmission expansion planning considering risk assessment of renewable energy extreme scenarios

An adaptive decision‐making approach for transmission expansion planning considering risk assessment of renewable energy extreme scenarios

Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants

An Adaptive Decision-making Approach for Transmission Expansion Planning Considering Risk Assessment of Renewable Energy Extreme Scenarios

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